Insulated
plastic
greenhouses
(IPG)
were
a
new
type
of
facility
emerging
in
production
China.
The
mechanism
construct
parameters
on
the
indoor
light
environmen.
This
paper
took
IPG
Shandong
area
as
research
object.
A
mathematical
model
was
established
to
simulate
environment
IPG.
can
well
describe
spatial
and
temporal
distribution
solar
radiation
greenhouse.
Based
this
model,
effects
multiple
parameters,
such
insulation
blanket
shading,
height‒span
ratio,
greenhouse
azimuth
geographical
latitude,
quantitatively
specified.
results
showed
that
inside
highly
variable
along
span
direction
simulation
data,
optimal
range
with
different
height
obtained.
And
by
simulating
under
angles,
it
found
accumulated
daily
reach
optimum
value
when
angle
is
0°
-
20°.
provide
theoretical
guidance
for
design
optimization
structure
Biosystems Engineering,
Год журнала:
2024,
Номер
243, С. 148 - 174
Опубликована: Май 29, 2024
Computational
fluid
dynamics
(CFD)
simulations
have
been
extensively
used
in
designing
air
distribution
systems
for
controlled
environment
agriculture
(CEA).In
recent
years,
more
application
studies
using
CFD
can
be
found
vertical
farms
due
to
the
increasing
interest
indoor
farming
systems.However,
it
is
well-known
that
are
sensitive
many
computational
parameters
and
settings.The
requirement
of
a
crop
response
model
simulation
farm
makes
even
complicated.Despite
increased
interest,
guidelines
scarce
based
on
literature
study.Therefore,
systematic
sensitivity
analysis
conducted
small
generic
multi-layer
with
sole
source
lighting,
which
was
object
study
before.The
impact
wide
range
physical
investigated,
including
grid
resolution,
turbulence
model,
intensity,
discretisation
scheme,
drag
coefficient
crops
time.The
shows
this
case
(inlet
Re
=
46,923,
Ar
0.078,
cultivated
lettuce),
RNG
k-ε
outperforms
other
commonly
two-equation
models.Compared
experimental
results
from
literature,
first-order
upwind
scheme
show
large
discrepancies,
especially
coarse
grid.Although
influence
airflow
inside
canopy
pronounced,
little
difference
observed
distributions
away
crops.
Numerical Heat Transfer Part A Applications,
Год журнала:
2024,
Номер
unknown, С. 1 - 25
Опубликована: Фев. 27, 2024
This
article
presents
a
comprehensive
examination
of
the
interior
environments
in
soilless
Greenhouse
located
Tunis
and
their
response
to
seasonal
variations.
The
research
employs
numerical
model
conjunction
with
an
experimental
setup
achieve
this
objective.
considers
various
elements,
including
glass,
air,
crops,
concrete
combination,
assess
impact
on
indoor
climate.
Rigorous
comparisons
data
collected
from
greenhouse
prototype,
particularly
regarding
parameters
like
air
velocity
temperature
profiles,
confirm
validity
findings.
To
closely
replicate
real
conditions,
underwent
optimization,
incorporating
turbulence
radiation
models
undergoing
grid
independence
analysis.
provides
thorough
analysis
how
fluctuations
directly
influence
microclimate
within
glass
greenhouse,
utilizing
combination
data.
Additionally,
series
simulations
were
conducted
evaluate
potential
crop
quantity
static
temperature.
comparative
revealed
that
difference
at
roof
level
between
scenarios
tomato
basil
cultivation
those
without
was
narrowed
down
3.5
K.
Consequently,
study
sheds
light
implications
climates
emphasizes
importance
accurate
modeling
control
optimize
agricultural
practices
northern
regions
Tunisia.
Agriculture,
Год журнала:
2024,
Номер
14(8), С. 1245 - 1245
Опубликована: Июль 28, 2024
In
the
process
of
agricultural
production
in
solar
greenhouses,
key
to
healthy
growth
greenhouse
crops
lies
accurately
predicting
environmental
conditions.
However,
there
are
complex
couplings
and
nonlinear
relationships
among
parameters.
This
study
independently
developed
a
acquisition
system
achieve
comprehensive
method
for
monitoring
environment.
Additionally,
it
proposed
multi-parameter
multi-node
prediction
model
greenhouses
based
on
Golden
Jackal
Optimization-Convolutional
Neural
Network-Bidirectional
Gated
Recurrent
Unit-Self-Attention
Mechanism
(GCBS).
The
GCBS
successfully
captures
environment
predicts
changes
carbon
dioxide
concentration,
air
temperature
humidity,
soil
at
different
location
nodes.
To
validate
performance
this
model,
we
employed
multiple
evaluation
metrics
conducted
comparative
analysis
with
four
baseline
models.
results
indicate
that,
while
exhibits
slightly
higher
computational
time
compared
traditional
Long
Short-Term
Memory
(LSTM)
network
series
prediction,
significantly
outperforms
LSTM
terms
accuracy
parameters,
achieving
improvements
76.89%,
69.37%,
59.83%,
56.72%,
respectively,
as
measured
by
Mean
Absolute
Error
(MAE)
metric.
Agronomy,
Год журнала:
2025,
Номер
15(3), С. 586 - 586
Опубликована: Фев. 27, 2025
The
temperature
distribution
of
the
cucumber
canopy
in
an
energy-saving
solar
greenhouse
was
simulated
this
study.
data
autumn
and
winter
were
collected
using
sensors,
spatial
heterogeneity
analyzed.
Utilizing
ground-based
LiDAR
scanning,
point
cloud
plant
canopies
acquired
to
construct
a
convex
hull
porous
model
leaf
organ
model.
Validation
against
real
measurements
revealed
model’s
superior
performance
over
hexahedral
computational
fluid
dynamics
(CFD)
simulations,
with
root
mean
square
error
0.71
°C
relative
2.9%,
as
opposed
0.99
4.3%,
respectively.
Simulations
scaled
virtual
demonstrated
reduced
variation
by
0.6
2.3
compared
particularly
provided
smooth
transition
among
leaves,
closely
approximating
actual
crop
conditions.
These
results
offer
insights
for
selection
CFD
modeling.
